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Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome. Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...

Cooperative Binding of Transcription Regulators

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Cis-regulatory Sequences

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

Cis-regulatory Sequences

Cis-regulatory Sequences

Epigenetic Regulation

Epigenetic Regulation

Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...

Epigenetic Regulation

Epigenetic Regulation

Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.

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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

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Optimization of regulatory DNA with active learning.

Yuxin Shen¹, Grzegorz Kudla², Diego A Oyarzún^1,3

¹School of Biological Sciences, University of Edinburgh, Edinburgh, UK.

Computational and Structural Biotechnology Journal

|October 27, 2025

Summary

This summary is machine-generated.

Active learning enhances DNA sequence design for biotechnology by iteratively optimizing protein expression. This machine learning approach outperforms traditional methods in complex biological landscapes, improving yields for engineered microbial strains.

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Area of Science:

Biotechnology
Synthetic Biology
Machine Learning

Background:

Biotechnology applications require microbial strains engineered for high heterologous protein expression.
Optimizing regulatory DNA elements is crucial for enhancing protein output.
Machine learning (ML) combined with high-throughput experimentation aids in finding improved regulatory sequences.

Purpose of the Study:

To explore active learning (AL) as a strategy for optimizing DNA sequences to improve protein expression levels.
To evaluate the performance and convergence of the AL loop in complex genotype-phenotype landscapes.

Main Methods:

Iterative cycles of measurements, ML model training, and sequence sampling/selection.
Utilized synthetic data and an experimentally validated yeast promoter sequence landscape.
Compared AL with one-shot optimization approaches.

Main Results:

Active learning demonstrated superior performance compared to one-shot optimization in complex, epistasis-rich landscapes.
AL effectively optimized sequences across different experimental conditions.
The framework showed potential for data integration across various settings (labs, strains, conditions).

Conclusions:

Active learning provides an effective framework for DNA sequence design and phenotype optimization in biotechnology.
AL offers a powerful strategy for maximizing protein yields in engineered microbial systems.